This invention relates generally to ligand-protein binding interactions and, more particularly, to methods for the optimization of antigen-antibody binding affinity.
Antibodies are heteromeric binding proteins generated by a vertebrate's immune system which bind to an antigen. The molecules are composed of two heavy and two light chains connected through disulfide bonds. Antibodies have a "Y"--shaped structure with the antigen binding portion being located at the end of both short arms of the Y. The region on the heavy and light chain polypeptides which corresponds to the antigen binding portion is known as the variable region. The binding specificity of an antibody is a composite of the antigen interactions with both heavy and light chain variable regions. The differences within this region are primarily responsible for the variation in binding specificities between antibodies.
The immune system has the capability of generating an almost infinite number of different antibodies. Such a large diversity is generated primarily through ontological recombination to form the variable regions of each chain and through differential pairing of heavy and light chains. Within the framework of the variable region of each chain are domains characterized by unusually divergent hypervariable sequences. These hypervariable region sequences are in large part responsible for antibody diversity since they constitute the antigen binding pocket within the native protein. Differences in amino acid sequences within these regions allow for the formation of different antigen-antibody binding interactions. Thus, the hypervariable variable region sequences complement the antigen functional groups and, as such, are also known as complementarity determining regions (CDRs). The ability to mimic the natural immune system by creating diverse combinations of CDR sequences would be of great value because it would allow for the rapid production of antibodies with high affinity to essentially any desired antigen. Such antibodies can be used for various diagnostic and therapeutic purposes.
Until recently, generation of antibodies against a desired molecule was accomplished only through manipulation of natural immune responses. Methods included classical immunization techniques of laboratory animals and monoclonal antibody production. Generation of monoclonal antibodies is laborious and time consuming. It involves a series of different techniques and is only performed on animal cells. Animal cells have relatively long generation times and require extra precautions to be taken to ensure viability of the cultures.
A method for the generation of a large repertoire of diverse antibody molecules in bacteria has also been described, Huse et al., Science 246:1275-1281 (1989), which is incorporated herein by reference. The method uses the bacteriophage lambda as the vector. The lambda vector is a long, linear double-stranded DNA molecule. Production of antibodies using this vector involves the cloning of heavy and light chain populations of DNA sequences into separate vectors. The vectors are subsequently combined randomly to form a single vector which directs the coexpression of heavy and light chains to form antibody fragments. A disadvantage to this method is that the antibody affinities are limited to in vivo derived affinities. This difference in affinities is due to a specific immunological affinity maturation process known as somatic mutation. Antibodies derived from recombinant libraries may not have benefited from this process. Additionally, antibody sequences may be disproportionally represented within the library due to the cloning process itself. An inherent outcome of this event can cause selection of only moderate affinity antibodies from the library if they predominate over the high affinity sequences.
There thus exists a need for a method to optimize antigen binding affinities which mimics the natural immunological processes and provides in vitro-derived antigen binding affinities different than those derived in vivo. The present invention satisfies these needs and provides related advantages as well.